Disease Progression Modeling and Equity for Diabetes
Irene Chen, Professor
Computational Precision Health
Closed. This professor is continuing with Fall 2023 apprentices on this project; no new apprentices needed for Spring 2024.
This project involves analyzing clinical data to better understand diabetes progression patterns and equity in diagnostic testing and treatment decisions
Role: The undergraduate researcher will review current clinical guidelines and literature on standard practices for diagnosing and monitoring patients with diabetes mellitus. They will then use statistical analysis and machine learning methods to model disease trajectories in longitudinal patient data, identifying subsets of patients with differing progression patterns. Additionally, the student will audit clinical decision making data to uncover potential disparities in diagnostic testing or treatment selections across patient demographics. Outcomes will include both improved predictive models to forecast diabetic complication risks and methodological contributions towards more equitable clinical protocols. This timely work will provide insights to enhance personalized care for diabetes patients while ensuring fairness in clinical practice.
Prof. Chen is an Assistant Professor in Computational Precision Health and Electrical Engineering and Computer Science. Her research group values curiosity, collaboration, compassion, and inclusion. We uphold rigorous standards of quality research and ethics, while ensuring each person is regarded first as a human with goals that are understood and supported. Our culture enables scholars to produce their best work.
Qualifications: Ideal candidates will be undergraduate students with coursework or experience in areas like machine learning, data science, and time-series data. The ability to code in Python is preferred. Students are expected to meet with the faculty mentor twice a week, and will be trained to conduct literature review, formulate research problems, and engage in scientific writing.
Hours: 12 or more hours
Related website: http://irenechen.net
Biological & Health Sciences Digital Humanities and Data Science